Abstract The ultimate goal of the proposed research is to develop a multiplex assay for early detection of Cutaneous T Cell Lymphoma (CTCL) in human serum or plasma. Mycosis fungoides (MF) is a slowly progressive form of CTCL that initially manifests by non-specific cutaneous eczematous patches and plaques, similar to atopic dermatitis (eczema), psoriasis, and other benign dermatoses. The early diagnosis of MF is frequently delayed by many years and many patients with early MF remain unrecognized, delaying appropriate therapy resulting in poor outcomes. Numerous attempts to improve diagnostic accuracy in early-stage disease have been made. Early diagnosis is particularly challenging due to absence of definitive markers for the disease, including unreliable clonality studies in early stages. Using a high throughput bead-based Luminex xMAP multiplexing technology, Dr. Geskin and colleagues have screened patients with MF for numerous potential biomarkers across all stages and compared them to normal controls, HIV patients, and patients with benign dermatoses in the age-matched fashion. They were able to demonstrate a distinct immune profile in patients with MF. Furthermore, measuring concentrations of a panel of several biomarkers in human plasma or serum would provide high sensitivity and specificity for distinguishing early-stage MF from non-MF controls. Our goal is to develop a non-invasive, simple multiplex assay-based screening test, which is capable of selecting the individuals at high-risk for cutaneous lymphoma among people with benign dermatoses before they develop advanced disease. Once a high risk group is selected, then an in-depth evaluation could be performed by diagnostic specialists. The Specific Aims of this Phase I project are: 1. To compare the performance of a multiplex assay for determination of several biomarkers in human plasma or serum with the corresponding singleplex ELISAs. 2. To show the feasibility of the multiplex assay for early detection of CTCL in human serum or plasma using a limited number of clinical samples.